FAUL, Stephen Daniel,TEMKO, Andriy,MARNANE, William, Peter,LIGHTBODY, Gordon,BOYLAN, Geraldine Bernadette
申请号：
DK10718103
公开号：
DK2416703T3
申请日:
2010.04.07
申请国别(地区):
DK
年份:
2016
代理人:
摘要：
The present invention relates to a method for the real-time identification of seizures in an Electroencephalogram (EEG) signal. The method provides for patient-independent seizure identification by use of a multi-patient trained generic Support Vector Machine (SVM) classifier. The SVM classifier is operates on a large feature vector combining features from a wide variety of signal processing and analysis techniques. The method operates sufficiently accurately to be suitable for use in a clinical environment. The method may also be combined with additional classifiers, such a Gaussian Mixture Model (GMM) classifier, for improved robustness, and one or more dynamic classifiers such as an SVM using sequential kernels for improved temporal analysis of the EEG signal.
